Abstract: A method and system are presented for identifying a customer in a commercial transaction using less than complete identifying information. A name for the customer is extracted from a credit card during a purchase transaction. A trade area for the point of sale location used to restrict a search of a demographic database to find a list of potential identity matches having names similar to the name on the credit card. A best match generator creates a profile of the expected purchaser of the products in the transaction. Using demographic information about each identity in the list of potential identity matches, each identity is compared to the profile and given a score. The highest scoring identity is then considered the best match. The best match identity is then assumed to be the identity involved in the transaction, and the customer database is updated to reflect this determination.

Abstract: A method and system are presented for identifying a customer in a commercial transaction using less than complete identifying information. A credit card purchase transaction is described wherein a name for the customer is removed from the credit card. A trade area is then determined for the point of sale utilizing historical sales at that point of sale. The trade area is then used to restrict a search of a demographic database to find a list of potential identity matches having names similar or identical to the name on the credit card. A best match generator then creates a profile of the expected purchaser of the products in the transaction. Using demographic information about each identity in the list of potential identity matches, each identity is compared to the profile and given a score. Scores can also be created by examining past purchases, or by examining the strength of the name match. The highest scoring identity is then considered the best match.